Finite-time synchronization for complex-valued recurrent neural networks with time delays
type: Item
instance of: scholarly article
title: Finite-time synchronization for complex-valued recurrent neural networks with time delays
zbMATH Open document ID: 1407.93058
DOI: 10.1155/2018/8456737
author: Ziye Zhang
author: Chong Lin
author: Xiaoping Liu
author: Bing Chen
published in: Complexity
publication date: 2019-02-19T00:00:00Z
review text: Summary: This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays. First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given. To achieve our aim, a nonlinear delayed controller with two independent parameters different from the existing ones is provided, which leads to great difficulty. To overcome it, a newly developed inequality is used. Then, via Lyapunov function approach, some criteria are derived to guarantee the finite-time synchronization of the considered system, and the settling time for synchronization is also estimated. Finally, two numerical simulations are given to support the effectiveness and advantages of the obtained results.
Mathematics Subject Classification ID: 93A14
Mathematics Subject Classification ID: 34D06
Mathematics Subject Classification ID: 92B20
Mathematics Subject Classification ID: 34H05
zbMATH DE Number: 7025194
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/8456737
OpenAlex ID: W2902860349
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Wikidata QID: Q128829022
description: scientific article; zbMATH DE number 7025194